The clinical significance of macrolide resistance in pediatric Mycoplasma pneumoniae infection during COVID-19 pandemic.

Background: Mycoplasma pneumoniae (MP) is a commonly occurring pathogen causing community-acquired pneumonia (CAP) in children. The global prevalence of macrolide-resistant MP (MRMP) infection, especially in Asian regions, is increasing rapidly. However, the prevalence of MRMP and its clinical significance during the COVID-19 pandemic is not clear. Methods: This study enrolled children with molecularly confirmed macrolide-susceptible MP (MSMP) and MRMP CAP from Beijing Children's Hospital Baoding Hospital, Capital Medical University between August 2021 and July 2022. The clinical characteristics, laboratory findings, chest imaging presentations, and strain genotypes were compared between patients with MSMP and MRMP CAP. Results: A total of 520 hospitalized children with MP-CAP were enrolled in the study, with a macrolide resistance rate of 92.7%. Patients with MRMP infection exhibited more severe clinical manifestations (such as dyspnea and pleural effusion) and had a longer hospital stay than the MSMP group. Furthermore, abnormal blood test results (including increased LDH and D-dimer) were more common in the MRMP group (P<0.05). Multilocus variable-number tandem-repeat analysis (MLVA) was performed on 304 samples based on four loci (Mpn13-16), and M3562 and M4572 were the major types, accounting for 74.0% and 16.8% of the strains, respectively. The macrolide resistance rate of M3562 strains was up to 95.1%. Conclusion: The prevalence of MRMP strains in hospitalized CAP patients was extremely high in the Baoding area, and patients infected with MRMP strains exhibited more severe clinical features and increased LDH and D-dimer. M3562 was the predominant resistant clone.

Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China

Ozone (O₃) is an important trace and greenhouse gas in the atmosphere, posing a threat to the ecological environment and human health at the ground level. Large-scale and long-term studies of O₃ pollution in China are few due to highly limited direct ground and satellite measurements. This study offers a new perspective to estimate ground-level O₃ from solar radiation intensity and surface temperature by employing an extended ensemble learning of the space-time extremely randomized trees (STET) model, together with ground-based observations, remote sensing products, atmospheric reanalysis, and an emission inventory. A full-coverage (100%), high-resolution (10 km) and high-quality daily maximum 8-h average (MDA8) ground-level O₃ dataset covering China (called ChinaHighO₃) from 2013 to 2020 was generated. Our MDA8 O₃ estimates (predictions) are reliable, with an average out-of-sample (out-of-station) coefficient of determination of 0.87 (0.80) and root-mean-square error of 17.10 (21.10) μg/m³ in China. The unique advantage of the full coverage of our dataset allowed us to accurately capture a short-term severe O₃ pollution exposure event that took place from 23 April to 8 May in 2020. Also, a rapid increase and recovery of O₃ concentrations associated with variations in anthropogenic emissions were seen during and after the COVID-19 lockdown, respectively. Trends in O₃ concentration showed an average growth rate of 2.49 μg/m³/yr (p < 0.001) from 2013 to 2020, along with the continuous expansion of polluted areas exceeding the daily O₃ standard (i.e., MDA8 O₃ = 160 μg/m³). Summertime O₃ concentrations and the probability of occurrence of daily O₃ pollution have significantly increased since 2015, especially in the North China Plain and the main air pollution transmission belt (i.e., the "2 + 26” cities). However, a decline in both was seen in 2020, mainly due to the coordinated control of air pollution and ongoing COVID-19 effects. This carefully vetted and smoothed dataset is valuable for studies on air pollution and environmental health in China.

Separating Daily 1 km PM2.5 Inorganic Chemical Composition in China since 2000 via Deep Learning Integrating Ground, Satellite, and Model Data.

Fine particulate matter (PM2.5) chemical composition has strong and diverse impacts on the planetary environment, climate, and health. These effects are still not well understood due to limited surface observations and uncertainties in chemical model simulations. We developed a four-dimensional spatiotemporal deep forest (4D-STDF) model to estimate daily PM2.5 chemical composition at a spatial resolution of 1 km in China since 2000 by integrating measurements of PM2.5 species from a high-density observation network, satellite PM2.5 retrievals, atmospheric reanalyses, and model simulations. Cross-validation results illustrate the reliability of sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and chloride (Cl-) estimates, with high coefficients of determination (CV-R2) with ground-based observations of 0.74, 0.75, 0.71, and 0.66, and average root-mean-square errors (RMSE) of 6.0, 6.6, 4.3, and 2.3 µg/m3, respectively. The three components of secondary inorganic aerosols (SIAs) account for 21% (SO42-), 20% (NO3-), and 14% (NH4+) of the total PM2.5 mass in eastern China; we observed significant reductions in the mass of inorganic components by 40-43% between 2013 and 2020, slowing down since 2018. Comparatively, the ratio of SIA to PM2.5 increased by 7% across eastern China except in Beijing and nearby areas, accelerating in recent years. SO42- has been the dominant SIA component in eastern China, although it was surpassed by NO3- in some areas, e.g., Beijing-Tianjin-Hebei region since 2016. SIA, accounting for nearly half (∼46%) of the PM2.5 mass, drove the explosive formation of winter haze episodes in the North China Plain. A sharp decline in SIA concentrations and an increase in SIA-to-PM2.5 ratios during the COVID-19 lockdown were also revealed, reflecting the enhanced atmospheric oxidation capacity and formation of secondary particles.

Alzheimer's disease and COVID-19: Interactions, intrinsic linkages, and the role of immunoinflammatory responses in this process.

Alzheimer's disease (AD) and COVID-19 share many common risk factors, such as advanced age, complications, APOE genotype, etc. Epidemiological studies have also confirmed the internal relationship between the two diseases. For example, studies have found that AD patients are more likely to suffer from COVID-19, and after infection with COVID-19, AD also has a much higher risk of death than other chronic diseases, and what's more interesting is that the risk of developing AD in the future is significantly higher after infection with COVID-19. Therefore, this review gives a detailed introduction to the internal relationship between Alzheimer's disease and COVID-19 from the perspectives of epidemiology, susceptibility and mortality. At the same time, we focused on the important role of inflammation and immune responses in promoting the onset and death of AD from COVID-19.

Suppression of ACE2 SUMOylation protects against SARS-CoV-2 infection through TOLLIP-mediated selective autophagy.

In addition to investigating the virology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), discovering the host-virus dependencies are essential to identify and design effective antiviral therapy strategy. Here, we report that the SARS-CoV-2 entry receptor, ACE2, conjugates with small ubiquitin-like modifier 3 (SUMO3) and provide evidence indicating that prevention of ACE2 SUMOylation can block SARS-CoV-2 infection. E3 SUMO ligase PIAS4 prompts the SUMOylation and stabilization of ACE2, whereas deSUMOylation enzyme SENP3 reverses this process. Conjugation of SUMO3 with ACE2 at lysine (K) 187 hampers the K48-linked ubiquitination of ACE2, thus suppressing its subsequent cargo receptor TOLLIP-dependent autophagic degradation. TOLLIP deficiency results in the stabilization of ACE2 and elevated SARS-CoV-2 infection. In conclusion, our findings suggest selective autophagic degradation of ACE2 orchestrated by SUMOylation and ubiquitination as a potential way to combat SARS-CoV-2 infection.

SARS-CoV-2-specific CD4+ T cell longevity correlates with Th17-like phenotype.

Determinants of memory T cell longevity following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection remain unknown. In addition, phenotypes associated with memory T cell longevity, antibody titers, and disease severity are incompletely understood. Here, we longitudinally analyzed SARS-CoV-2-specific T cell and antibody responses of a unique cohort with similar numbers of mild, moderate, and severe coronavirus disease 2019 cases. The half-lives of CD4+ and CD8+ T cells were longer than those of antibody titers and showed no clear correlation with disease severity. When CD4+ T cells were divided into Th1-, Th2-, Th17-, and Tfh-like subsets, the Th17-like subset showed a longer half-life than other subsets, indicating that Th17-like cells are most closely correlated with T cell longevity. In contrast, Th2- and Tfh-like T cells were more closely correlated with antibody titers than other subsets. These results suggest that distinct CD4+ T cell subsets are associated with longevity and antibody responses.

Ground-Level NO2 Surveillance from Space Across China for High Resolution Using Interpretable Spatiotemporally Weighted Artificial Intelligence.

Nitrogen dioxide (NO2) at the ground level poses a serious threat to environmental quality and public health. This study developed a novel, artificial intelligence approach by integrating spatiotemporally weighted information into the missing extra-trees and deep forest models to first fill the satellite data gaps and increase data availability by 49% and then derive daily 1 km surface NO2 concentrations over mainland China with full spatial coverage (100%) for the period 2019-2020 by combining surface NO2 measurements, satellite tropospheric NO2 columns derived from TROPOMI and OMI, atmospheric reanalysis, and model simulations. Our daily surface NO2 estimates have an average out-of-sample (out-of-city) cross-validation coefficient of determination of 0.93 (0.71) and root-mean-square error of 4.89 (9.95) µg/m3. The daily seamless high-resolution and high-quality dataset "ChinaHighNO2" allows us to examine spatial patterns at fine scales such as the urban-rural contrast. We observed systematic large differences between urban and rural areas (28% on average) in surface NO2, especially in provincial capitals. Strong holiday effects were found, with average declines of 22 and 14% during the Spring Festival and the National Day in China, respectively. Unlike North America and Europe, there is little difference between weekdays and weekends (within ±1 µg/m3). During the COVID-19 pandemic, surface NO2 concentrations decreased considerably and then gradually returned to normal levels around the 72nd day after the Lunar New Year in China, which is about 3 weeks longer than the tropospheric NO2 column, implying that the former can better represent the changes in NOx emissions.

Integrated store service quality measurement scale in omni-channel retailing

Purpose>Brick-and-mortar store is an essential channel to deliver a seamless shopping experience and meet customer's dynamic needs in omni-channel retailing. This paper aims to understand customers' expectations of the integrated stores and develop a measurement scale to assess in-store service quality in omni-channel retailing.Design/methodology/approach>Grounded theory methodology (GTM) is employed to obtain a clear picture of consumer expectations and preferences regarding the omni-channel brick-and-mortar integrated stores. Then, an integrated store service quality scale is proposed, refined and validated using a questionnaire survey and structural equation model (SEM).Findings>The measurement scale is set to include seven dimensions: in-store environment, in-store technology, product information consistency, employee assistance, personalization, channel availability and instant gratification and return. The relationships among these seven dimensions and customer satisfaction and loyalty are also verified. According to SEM, product information consistency is more important for customer satisfaction while personalization contributes more to customer loyalty. The results demonstrate that by analysing the seven dimensions, retailers can better understand customers and further improve service quality.Originality/value>This paper proposes a sufficient measurement scale for in-store service quality and fills the gap in omni-channel retailing by capturing its integration attribute.

Investor Sentiment and Stock Market Reactions to COVID-19: Evidence from China

This paper treats the outbreak of coronavirus disease 2019 (COVID-19) as a natural experiment that can provide insights into the effects of investor sentiment on stock market reactions. Employing the event study methodology (ESM) and taking the date of the Wuhan lockdown as the event date, we find that average abnormal return (AAR) and cumulative abnormal return (CAR) are significantly negative, and average trading volume excesses far more than before within two days of the outbreak. Further, we establish a difference-in-differences (DID) model to investigate the differences between Hubei and non-Hubei listed companies. The results show that for Hubei listed companies, the change of excessive trading volume (ETV) between pre-event and post-event period is significantly higher than that of non-Hubei listed companies, while there exhibits no relationship between the change of AAR and registration place. Overall, our findings provide new evidence for the interaction of local bias and investor sentiment affecting stock market reactions. [ FROM AUTHOR] Copyright of Discrete Dynamics in Nature & Society is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Distinct immune cell dynamics correlate with the immunogenicity and reactogenicity of SARS-CoV-2 mRNA vaccine.

Two doses of Pfizer/BioNTech BNT162b2 mRNA vaccine elicit robust severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-neutralizing antibodies with frequent adverse events. Here, by applying a high-dimensional immune profiling on 92 vaccinees, we identify six vaccine-induced immune dynamics that correlate with the amounts of neutralizing antibodies, the severity of adverse events, or both. The early dynamics of natural killer (NK)/monocyte subsets (CD16+ NK cells, CD56high NK cells, and non-classical monocytes), dendritic cell (DC) subsets (DC3s and CD11c- Axl+ Siglec-6+ [AS]-DCs), and NKT-like cells are revealed as the distinct cell correlates for neutralizing-antibody titers, severity of adverse events, and both, respectively. The cell correlates for neutralizing antibodies or adverse events are consistently associated with elevation of interferon gamma (IFN-γ)-inducible chemokines, but the chemokine receptors CCR2 and CXCR3 are expressed in distinct manners between the two correlates: vaccine-induced expression on the neutralizing-antibody correlate and constitutive expression on the adverse-event correlate. The finding may guide vaccine strategies that balance immunogenicity and reactogenicity.

Newly Emerging Strategies in Antiviral Drug Discovery: Dedicated to Prof. Dr. Erik De Clercq on Occasion of His 80th Anniversary.

Viral infections pose a persistent threat to human health. The relentless epidemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global health problem, with millions of infections and fatalities so far. Traditional approaches such as random screening and optimization of lead compounds by organic synthesis have become extremely resource- and time-consuming. Various modern innovative methods or integrated paradigms are now being applied to drug discovery for significant resistance in order to simplify the drug process. This review provides an overview of newly emerging antiviral strategies, including proteolysis targeting chimera (PROTAC), ribonuclease targeting chimera (RIBOTAC), targeted covalent inhibitors, topology-matching design and antiviral drug delivery system. This article is dedicated to Prof. Dr. Erik De Clercq, an internationally renowned expert in the antiviral drug research field, on the occasion of his 80th anniversary.

SARS-CoV-2 Omicron-neutralizing memory B cells are elicited by two doses of BNT162b2 mRNA vaccine.

Multiple SARS-CoV-2 variants have mutations in the spike receptor binding domain (RBD) with potential to evade neutralizing antibody. In particular, the Beta and Omicron variants escape from antibody neutralizing activity in those who received two doses of BNT162b2 mRNA vaccine. Nonetheless, boosting with a third vaccine dose or by breakthrough infection improves the overall breadth of the neutralizing antibodies, but the mechanism remains unclear. Here, we longitudinally profiled the cellular composition of RBD-binding memory B cell subsets and their antibody binding and neutralizing activity against SARS-CoV-2 variants after the second dose of mRNA vaccine. Two doses of the mRNA vaccine elicited plasma neutralizing antibodies with a limited activity against Beta and Omicron but induced an expanded antibody breadth overtime, up to 4.9 months after vaccination. In contrast, more than one-third of RBD-binding IgG+ memory B cells with a resting phenotype initially bound the Beta and Omicron variants and steadily increased the B cell receptor breadth overtime. As a result, a fraction of the resting memory B cell subset secreted Beta and Omicron-neutralizing antibody when stimulated in vitro. The neutralizing breadth of the resting memory B cell subset helps us understand the prominent recall of Omicron-neutralizing antibodies after an additional booster or breakthrough infection in fully vaccinated individuals.

Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China

Ozone (O3) is an important trace and greenhouse gas in the atmosphere, posing a threat to the ecological environment and human health at the ground level. Large-scale and long-term studies of O3 pollution in China are few due to highly limited direct ground and satellite measurements. This study offers a new perspective to estimate ground-level O3 from solar radiation intensity and surface temperature by employing an extended ensemble learning of the space-time extremely randomized trees (STET) model, together with ground-based observations, remote sensing products, atmospheric reanalysis, and an emission inventory. A full-coverage (100%), high-resolution (10 km) and high-quality daily maximum 8-h average (MDA8) ground-level O3 dataset covering China (called ChinaHighO3) from 2013 to 2020 was generated. Our MDA8 O3 estimates (predictions) are reliable, with an average out-of-sample (out-of-station) coefficient of determination of 0.87 (0.80) and root-mean-square error of 17.10 (21.10) μg/m3 in China. The unique advantage of the full coverage of our dataset allowed us to accurately capture a short-term severe O3 pollution exposure event that took place from 23 April to 8 May in 2020. Also, a rapid increase and recovery of O3 concentrations associated with variations in anthropogenic emissions were seen during and after the COVID-19 lockdown, respectively. Trends in O3 concentration showed an average growth rate of 2.49 μg/m3/yr (p < 0.001) from 2013 to 2020, along with the continuous expansion of polluted areas exceeding the daily O3 standard (i.e., MDA8 O3 = 160 μg/m3). Summertime O3 concentrations and the probability of occurrence of daily O3 pollution have significantly increased since 2015, especially in the North China Plain and the main air pollution transmission belt (i.e., the “2 + 26” cities). However, a decline in both was seen in 2020, mainly due to the coordinated control of air pollution and ongoing COVID-19 effects. This carefully vetted and smoothed dataset is valuable for studies on air pollution and environmental health in China.

Increased in vitro neutralizing activity of SARS-CoV-2 IgA1 dimers compared to monomers and IgG.

Here, we expressed two neutralizing monoclonal antibodies (Abs) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; H4 and B38) in three formats: IgG1, IgA1 monomers (m), and IgA1 dimers (d) in glycoengineered Nicotiana benthamiana plants. All six Ab variants assembled properly and exhibited a largely homogeneous glycosylation profile. Despite modest variation in antigen binding between Ab formats, SARS-CoV-2 neutralization (NT) potency significantly increased in the following manner: IgG1 < IgA1-m < IgA1-d, with an up to 240-fold NT increase of dimers compared to corresponding monomers. Our results underscore that both IgA's structural features and multivalency positively impact NT potency. In addition, they emphasize the versatile use of plants for the rapid expression of complex human proteins.

Highly active engineered IgG3 antibodies against SARS-CoV-2.

Monoclonal antibodies (mAbs) that efficiently neutralize SARS-CoV-2 have been developed at an unprecedented speed. Notwithstanding, there is a vague understanding of the various Ab functions induced beyond antigen binding by the heavy-chain constant domain. To explore the diverse roles of Abs in SARS-CoV-2 immunity, we expressed a SARS-CoV-2 spike protein (SP) binding mAb (H4) in the four IgG subclasses present in human serum (IgG1-4) using glyco-engineered Nicotiana benthamiana plants. All four subclasses, carrying the identical antigen-binding site, were fully assembled in planta and exhibited a largely homogeneous xylose- and fucose-free glycosylation profile. The Ab variants ligated to the SP with an up to fivefold increased binding activity of IgG3. Furthermore, all H4 subtypes were able to neutralize SARS-CoV-2. However, H4-IgG3 exhibited an up to 50-fold superior neutralization potency compared with the other subclasses. Our data point to a strong protective effect of IgG3 Abs in SARS-CoV-2 infection and suggest that superior neutralization might be a consequence of cross-linking the SP on the viral surface. This should be considered in therapy and vaccine development. In addition, we underscore the versatile use of plants for the rapid expression of complex proteins in emergency cases.

Medicinal chemistry strategies towards the development of effective SARS-CoV-2 inhibitors.

Novel therapies are urgently needed to improve global treatment of SARS-CoV-2 infection. Herein, we briefly provide a concise report on the medicinal chemistry strategies towards the development of effective SARS-CoV-2 inhibitors with representative examples in different strategies from the medicinal chemistry perspective.

A SARS-CoV-2 antibody broadly neutralizes SARS-related coronaviruses and variants by coordinated recognition of a virus-vulnerable site.

Potent neutralizing SARS-CoV-2 antibodies often target the spike protein receptor-binding site (RBS), but the variability of RBS epitopes hampers broad neutralization of multiple sarbecoviruses and drifted viruses. Here, using humanized mice, we identified an RBS antibody with a germline VH gene that potently neutralized SARS-related coronaviruses, including SARS-CoV and SARS-CoV-2 variants. X-ray crystallography revealed coordinated recognition by the heavy chain of non-RBS conserved sites and the light chain of RBS with a binding angle mimicking the angiotensin-converting enzyme 2 (ACE2) receptor. The minimum footprints in the hypervariable region of RBS contributed to the breadth of neutralization, which was enhanced by immunoglobulin G3 (IgG3) class switching. The coordinated binding resulted in broad neutralization of SARS-CoV and emerging SARS-CoV-2 variants of concern. Low-dose therapeutic antibody treatment in hamsters reduced the virus titers and morbidity during SARS-CoV-2 challenge. The structural basis for broad neutralizing activity may inform the design of a broad spectrum of therapeutics and vaccines.

Search, Identification, and Design of Effective Antiviral Drugs Against Pandemic Human Coronaviruses.

Recent coronavirus outbreaks of SARS-CoV-1 (2002-2003), MERS-CoV (since 2012), and SARS-CoV-2 (since the end of 2019) are examples of how viruses can damage health care and generate havoc all over the world. Coronavirus can spread quickly from person to person causing high morbidity and mortality. Unfortunately, the antiviral armamentarium is insufficient to fight these infections. In this chapter, we provide a detailed summary of the current situation in the development of drugs directed against pandemic human coronaviruses. Apart from the recently licensed remdesivir, other antiviral agents discussed in this review include molecules targeting viral components (e.g., RNA polymerase inhibitors, entry inhibitors, or protease inhibitors), compounds interfering with virus-host interactions, and drugs identified in large screening assays, effective against coronavirus replication, but with an uncertain mechanism of action.

Temporal maturation of neutralizing antibodies in COVID-19 convalescent individuals improves potency and breadth to circulating SARS-CoV-2 variants.

Antibody titers against SARS-CoV-2 slowly wane over time. Here, we examined how time affects antibody potency. To assess the impact of antibody maturation on durable neutralizing activity against original SARS-CoV-2 and emerging variants of concern (VOCs), we analyzed receptor binding domain (RBD)-specific IgG antibodies in convalescent plasma taken 1-10 months after SARS-CoV-2 infection. Longitudinal evaluation of total RBD IgG and neutralizing antibody revealed declining total antibody titers but improved neutralization potency per antibody to original SARS-CoV-2, indicative of antibody response maturation. Neutralization assays with authentic viruses revealed that early antibodies capable of neutralizing original SARS-CoV-2 had limited reactivity toward B.1.351 (501Y.V2) and P.1 (501Y.V3) variants. Antibodies from late convalescents exhibited increased neutralization potency to VOCs, suggesting persistence of cross-neutralizing antibodies in plasma. Thus, maturation of the antibody response to SARS-CoV-2 potentiates cross-neutralizing ability to circulating variants, suggesting that declining antibody titers may not be indicative of declining protection.

False-positive colloidal gold-based immunochromatographic strip assay reactions for antibodies to SARS-CoV-2 in patients with autoimmune diseases.

BACKGROUND: The outbreak of the novel 2019 coronavirus disease (COVID-19) was declared a global pandemic by the World Health Organization (WHO) on March 11, 2020. The diagnosis of COVID-19 is frequently based on a positive serological test. We noted the occurrence of false-positive results for COVID-19 in the colloidal gold-based immunochromatographic strip (ICS) assay in sera from patients with autoimmune diseases (ADs). This study aimed to evaluate the possible reasons for the false-positive results in two ICS assays (Wondfo ICS and Innovita ICS) and to investigate the effect of urea dissociation in reducing false-positive results. METHODS: The sera of 135 patients with ADs, 13 confirmed COVID-19 patients, 95 disease controls, and 120 healthy controls were tested for immunoglobin M (IgM) and IgG against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using Wondfo and Innovita ICS kits. The distributions of auto-antibodies in antibody-positive and antibody-negative groups were also compared, and bivariable logistic regression was used to assess auto-antibodies associated with false-positive results. A urea dissociation test of ICS was performed for the SARS-CoV-2 antibody-positive samples. RESULTS: Specificity of Wondfo ICS for the 95 disease controls was 94.74% compared to 98.95% and 96.84% for Innovita SARS-CoV-2 IgM and IgG, respectively. Specificity of Wondfo ICS for the 120 healthy controls was 97.5% compared to 100% and 99.17% for Innovita SARS-CoV-2 IgM and IgG, respectively. Specificity of Wondfo ICS for AD patients was 73.33% compared to 97.78% and 96.30% for Innovita SARS-CoV-2 IgM and IgG, respectively. Sensitivity was 74.07% for Wondfo compared to 70.37% for Innovita IgM and 66.67% for Innovita IgG. Using the Wondfo ICS, the percentage of elevated rheumatoid factor (RF) level (>20 IU/mL) was higher in the SARS-CoV-2 antibody-positive group compared with the antibody-negative group [27/36 (75.0%) vs. 34/99 (34.34%), P=0.001]. The elevated RF was associated with antibody positivity, with an odds ratio of 4.671 [95% confidence interval (CI), 1.88-11.69]. The specificity of the Wondfo ICS assay for the AD patients was increased from 73.33% to 94.07% after the urea dissociation assay. CONCLUSIONS: An elevated serum RF level could lead to false-positive results when detecting SARS-CoV-2 antibodies using the Wondfo ICS kit, and the urea dissociation assay would be helpful in reducing the incidence of false-positive results.